This is because, aforloop takes an iterator and iterates over it usingnext()function. It automatically ends whenStopIterationis raised. Check here toknow how a for loop is actually implemented in Python. 我们也可以用循环来调用,这里可以去理解一下Python的循环的实现原理。 # A simple generator fu...
Example 2: Python Generator Expression # create the generator object squares_generator = (i * i for i in range(5)) # iterate over the generator and print the values for i in squares_generator: print(i) Run Code Output 0 1 4 9 16 Here, we have created the generator object that wil...
1defgenerator():2yield13yield2456a=generator()7printa.next()8printa.next() 输出1,2。 这里,a=generator()不是执行函数,而是生成了一个生成器对象。 生成器就是一种迭代器。 所以生成器也有next()方法,也可以用for ... in ... 1classText8Corpus(object):2"""Iterate over sentences from the "t...
生成器 生成器是迭代器,但你只能遍历它一次(iterate over them once) 因为生成器并没有将所有值放入内存中,而是实时地生成这些值 mygenerator=(x*xforxinrange(3))# 生成器# mygenerator = [x * x for x in range(3)] # 列表foriinmygenerator:print("i=",i)foriinmygenerator:print("New=",i) ...
active_items = set() inactive_items = set() # Iterate over all items for item in chain(active_items, inactive_items): # Process item 这当然比写两个单独的循环要优雅许多。 chain() 接受一个或多个可迭代对象作为输入的参数,然后创建一个迭代器,依次返回每个迭代器中的元素。这种方法比将两个对象...
the fly. You use them by iterating over them, either with a ‘for’ loop or by passing them to any function or construct that iterates. Most of the timegeneratorsare implemented as functions. However, they do notreturna value, theyyieldit. Here is a simple example of ageneratorfunction...
生成器是迭代器,但你只能遍历它一次(iterate over them once) 因为生成器并没有将所有值放入内存中,而是实时地生成这些值 >>> mygenerator = (x*x for x in range(3)) >>> for i in mygenerator: ... print(i) 0 1 4 这和使用列表解析地唯一区别在于使用()替代了原来的[] 注意,你不能执行for ...
A Python object which can be looped over or iterated over in a loop. Examples of iterables include lists, sets, tuples, dictionaries, strings, etc. Iterator An iterator is an object that can be iterated upon. Thus, iterators contain a countable number of values. Generator A special ...
A generator is a function that produces a sequence of results instead of a single value. def yrange(n): i = 0 while i < n: yield i i += 1 Each time the yield statement is executed the function generates a new value. >>> y = yrange(3) >>> y <generator object yrange at ...
<generator object countdown at 0x7fd33ac44200> >>> 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 一个生成器函数主要特征是它只会回应在迭代中使用到的 next 操作。一旦生成器函数返回退出,迭代终止。